ArticleFrontiers in oncology2021
Comprehensive Bioinformatics Analysis to Identify the Gene HMMR Associated With Lung Adenocarcinoma Prognosis and Its Mechanism of Action in Multiple Cancers.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- HMMR in human cancers: regulatory mechanism and biological function.Journal of translational medicine · 2025Review
- Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Article
- Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes.Annals of medicine · 2022Article
- Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures.Frontiers in oncology · 2022Article
- Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis.Frontiers in immunology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung cancer is the third most frequently diagnosed cancer in the world, with lung adenocarcinoma (LUAD) as the most common pathological type. But studies on the predictive effect of a single gene on LUAD are limited. We aimed to discover new predictive markers for LUAD.
methodsDifferentially high-expressed genes at each stage were obtained from the TCGA and GTEx databases. The functions of these genes were investigated through GO enrichment and KEGG pathway analyses. Then, the key genes were selected by applying whole gene overall survival time. The expression of the key gene was studied in LUAD, and survival analysis was performed using Kaplan-Meier mapper, followed by univariate and multifactorial COX analysis. Finally, the gene expression and its prognostic significance in the pan-cancer were examined.
resultsA total of 10,106 DEGs were obtained from the two datasets. The top 266 differentially upregulated genes intersected with the top 1,497 overall survival-related genes, and 87 key genes were identified. High-expressed HMMR was associated with a poor prognosis of LUAD. Univariate and multifactorial Cox analysis showed that HMMR was an independent prognostic factor for LUAD patients. A high HMMR expression was strongly associated with the overall survival (OS) and disease-specific survival (DSS) in 11 cancer types and with poorer OS, DSS, and PFI in 10 cancer types.
conclusionHMMR may be an independent prognostic indicator and an important biomarker in diagnosing and predicting the survival of LUAD patients. Also, HMMR may be a key predictor of a variety of cancers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.